PDF and Office documents
A defined part of a concept tailored to the use case.
Individually configured
AI Knowledge Base
How does an AI knowledge base work?
An AI knowledge base makes selected documents usable for natural-language questions. Suitable content is prepared, indexed and governed by access rules. Answers can refer to the source passages used; quality and completeness must be reviewed continuously.
Building blocks
What is addressed in the concept.
Sources and RAG
A defined part of a concept tailored to the use case.
Permissions and indexing
A defined part of a concept tailored to the use case.
How we approach it
First clarify the value. Then select the technology to fit.
The starting point is a realistic task: which questions should employees clarify faster, which sources are suitable and what role does AI play in the existing process? This is followed by data review, configuration, testing and guided rollout.
RAG explained
View the project processRetrieval-augmented generation connects a language model to a separate knowledge base. Relevant information is retrieved for a question and supplied as context. This can ground answers in selected sources, but it does not replace quality review.
Frequently asked questions
Decision-relevant points before starting.
Suitability always depends on the intended use.
No. The platform is aligned to the agreed use case, suitable data sources, roles and operating model. The exact scope is defined before implementation.
The AI supports search, summarisation and drafts. Responsible people review results and make decisions.
That depends on the goal, data situation, permissions and infrastructure. A limited, well-prepared initial scope is usually the most useful first step.